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Author Choy, Marian ♦ Jin, Jesse S.
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Semi-automatic Method ♦ Morphological Segmentation ♦ Morphological Image Analysis ♦ Edge Point ♦ Overall Procedure ♦ Data Set ♦ Second Derivative Operator ♦ Left-ventricular Endocardial Border ♦ Morphological Filtering ♦ Echocardiographic Image ♦ Second Order Filtering ♦ Endocardial Border ♦ Accurate Identification ♦ Boundary Detection ♦ Modphological Image Analysis ♦ Correlation Coefficient ♦ Cardiac Function ♦ Root Mean Square Error
Description Assessment of cardiac function using imaging techniques requires accurate identification of borders. We have developed a semi-automatic method for boundary detection of echocardiographic images. Our method combines morphological image analysis techniques with a second derivative operator, namely Laplican of Gaussian. Morphological filtering is used to reduce noise and increase contrast of the image. Results of second order filtering is used to locate edge points, as well as incorporate with morphological segmentation to extract the contour. We validate the results by comparing the computer generated contours to the contours manually outlined by an expert on the data sets. The average of the root mean square errors of the distances is 2.56 pixels (oe = 1.21 pixels) for the endocardial borders. The correlation coefficient between the areas enclosed is 0.99. Thus, by using modphological image analysis in echocardiographic images, the overall procedure is simple, efficient, and produces en...
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 1996-01-01
Publisher Institution In SPIE Proceedings on Medical Imaging